Systems and methods for concept based searching or recommendation are disclosed. More particularly, embodiments of a concept based approach to the search and analysis of data, including the creation, update or use of concept networks in searching and analyzing data are disclosed, including embodiments of the usage of such concept networks in artificial intelligence systems that are capable of utilizing concepts expressed by users to return or evaluate associated images.
Legal claims defining the scope of protection, as filed with the USPTO.
2. The system of claim 1, wherein determining the destination associated with the canonical concept is determined comprises: determining a score for the canonical concept for each destination in the set of destinations, wherein determining a score for the canonical concept for the destination comprises accessing the destination concept vector associated with the destination to determine the score for the canonical concept for the destination and selecting the destination based on the score for the canonical concept for each destination in the set of destinations.
3. The system of claim 1, wherein the destination is a neighborhood, apartment, or house.
4. The system of claim 1, wherein the current interaction is a natural language interaction.
5. The system of claim 1, wherein the image concept vector for the image was determined by: determining one or more concepts associated with the image; determining a score for the one or more concepts associated with the image and applying the score for the one or more concepts associated with the image to a concept net relationship matrix.
6. The system of claim 1, wherein the canonical concept is based on one or more previous user interactions in a session associated with the user.
7. The system of claim 1, wherein the image is selected based on its similarity to other images in the set of images.
9. The non-transitory computer readable medium of claim 8, wherein determining the destination associated with the canonical concept is determined comprises: determining a score for the canonical concept for each destination in the set of destinations, wherein determining a score for the canonical concept for the destination comprises accessing the destination concept vector associated with the destination to determine the score for the canonical concept for the destination and selecting the destination based on the score for the canonical concept for each destination in the set of destinations.
10. The non-transitory computer readable medium of claim 8, wherein the destination is a neighborhood, apartment, or house.
11. The non-transitory computer readable medium of claim 8, wherein the current interaction is a natural language interaction.
12. The non-transitory computer readable medium of claim 8, wherein the image concept vector for the image was determined by: determining one or more concepts associated with the image; determining a score for the one or more concepts associated with the image and applying the score for the one or more concepts associated with the image to a concept net relationship matrix.
13. The non-transitory computer readable medium of claim 8, wherein the canonical concept is based on one or more previous user interactions in a session associated with the user.
14. The non-transitory computer readable medium of claim 8, wherein the image is selected based on its similarity to other images in the set of images.
16. The method of claim 15, wherein determining the destination associated with the canonical concept is determined comprises: determining a score for the canonical concept for each destination in the set of destinations, wherein determining a score for the canonical concept for the destination comprises accessing the destination concept vector associated with the destination to determine the score for the canonical concept for the destination and selecting the destination based on the score for the canonical concept for each destination in the set of destinations.
17. The method of claim 15, wherein the destination is a neighborhood, apartment, or house.
18. The method of claim 15, wherein the current interaction is a natural language interaction.
19. The method of claim 15, wherein the image concept vector for the image was determined by: determining one or more concepts associated with the image; determining a score for the one or more concepts associated with the image and applying the score for the one or more concepts associated with the image to a concept net relationship matrix.
20. The method of claim 15, wherein the canonical concept is based on one or more previous user interactions in a session associated with the user.
21. The method of claim 15, wherein the image is selected based on its similarity to other images in the set of images.
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November 13, 2020
October 25, 2022
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